Exploratory Data Analysis

Dataset statistics

Number of variables	27
Number of observations	1000
Missing cells	3199
Missing cells (%)	11.8%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	251.0 KiB
Average record size in memory	257.1 B

Variable types

Numeric	4
Categorical	23

Alerts

`Telephone` has constant value "Registered under the applicant's name"	Constant
`loan_application_id` has a high cardinality: 1000 distinct values	High cardinality
`Months_loan_taken_for` is highly correlated with `Principal_loan_amount`	High correlation
`Principal_loan_amount` is highly correlated with `Months_loan_taken_for`	High correlation
`Months_loan_taken_for` is highly correlated with `Principal_loan_amount`	High correlation
`Principal_loan_amount` is highly correlated with `Months_loan_taken_for`	High correlation
`applicant_id` is highly correlated with `Number_of_dependents` and 5 other fields	High correlation
`Primary_applicant_age_in_years` is highly correlated with `Number_of_dependents` and 4 other fields	High correlation
`Number_of_dependents` is highly correlated with `applicant_id` and 5 other fields	High correlation
`Years_at_current_residence` is highly correlated with `Foreign_worker` and 3 other fields	High correlation
`Foreign_worker` is highly correlated with `applicant_id` and 7 other fields	High correlation
`Months_loan_taken_for` is highly correlated with `Has_coapplicant` and 1 other fields	High correlation
`Principal_loan_amount` is highly correlated with `EMI_rate_in_percentage_of_disposable_income` and 3 other fields	High correlation
`EMI_rate_in_percentage_of_disposable_income` is highly correlated with `Principal_loan_amount` and 4 other fields	High correlation
`Has_coapplicant` is highly correlated with `applicant_id` and 10 other fields	High correlation
`Has_guarantor` is highly correlated with `applicant_id` and 10 other fields	High correlation
`Number_of_existing_loans_at_this_bank` is highly correlated with `applicant_id` and 5 other fields	High correlation
`high_risk_applicant` is highly correlated with `applicant_id` and 9 other fields	High correlation
`Other_EMI_plans` is highly correlated with `Telephone`	High correlation
`EMI_rate_in_percentage_of_disposable_income` is highly correlated with `Telephone`	High correlation
`Telephone` is highly correlated with `Other_EMI_plans` and 20 other fields	High correlation
`Savings_account_balance` is highly correlated with `Telephone`	High correlation
`Number_of_dependents` is highly correlated with `Telephone`	High correlation
`Property` is highly correlated with `Telephone`	High correlation
`Has_been_employed_for_at_most` is highly correlated with `Telephone` and 1 other fields	High correlation
`Balance_in_existing_bank_account_(upper_limit_of_bucket)` is highly correlated with `Telephone` and 1 other fields	High correlation
`Loan_history` is highly correlated with `Telephone`	High correlation
`Purpose` is highly correlated with `Telephone`	High correlation
`Has_guarantor` is highly correlated with `Telephone`	High correlation
`high_risk_applicant` is highly correlated with `Telephone`	High correlation
`Has_coapplicant` is highly correlated with `Telephone`	High correlation
`Balance_in_existing_bank_account_(lower_limit_of_bucket)` is highly correlated with `Telephone` and 1 other fields	High correlation
`Foreign_worker` is highly correlated with `Telephone`	High correlation
`Housing` is highly correlated with `Telephone`	High correlation
`Marital_status` is highly correlated with `Telephone` and 1 other fields	High correlation
`Has_been_employed_for_at_least` is highly correlated with `Telephone` and 1 other fields	High correlation
`Gender` is highly correlated with `Telephone` and 1 other fields	High correlation
`Years_at_current_residence` is highly correlated with `Telephone`	High correlation
`Number_of_existing_loans_at_this_bank` is highly correlated with `Telephone`	High correlation
`Employment_status` is highly correlated with `Telephone`	High correlation
`Gender` is highly correlated with `Marital_status`	High correlation
`Marital_status` is highly correlated with `Gender`	High correlation
`Years_at_current_residence` is highly correlated with `Has_been_employed_for_at_least`	High correlation
`Employment_status` is highly correlated with `Has_been_employed_for_at_most`	High correlation
`Has_been_employed_for_at_least` is highly correlated with `Years_at_current_residence` and 1 other fields	High correlation
`Has_been_employed_for_at_most` is highly correlated with `Employment_status` and 1 other fields	High correlation
`Months_loan_taken_for` is highly correlated with `Principal_loan_amount`	High correlation
`Principal_loan_amount` is highly correlated with `Months_loan_taken_for`	High correlation
`Has_been_employed_for_at_least` has 62 (6.2%) missing values	Missing
`Has_been_employed_for_at_most` has 253 (25.3%) missing values	Missing
`Telephone` has 596 (59.6%) missing values	Missing
`Savings_account_balance` has 183 (18.3%) missing values	Missing
`Balance_in_existing_bank_account_(lower_limit_of_bucket)` has 668 (66.8%) missing values	Missing
`Balance_in_existing_bank_account_(upper_limit_of_bucket)` has 457 (45.7%) missing values	Missing
`Purpose` has 12 (1.2%) missing values	Missing
`Property` has 154 (15.4%) missing values	Missing
`Other_EMI_plans` has 814 (81.4%) missing values	Missing
`loan_application_id` is uniformly distributed	Uniform
`applicant_id` has unique values	Unique
`loan_application_id` has unique values	Unique

Reproduction

Analysis started	2022-09-16 07:18:20.714216
Analysis finished	2022-09-16 07:18:55.259404
Duration	34.55 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

applicant_id
Real number (ℝ_≥0)

HIGH CORRELATION
UNIQUE

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1514763.121

Minimum	1105364
Maximum	1903505
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	47.9 KiB

Quantile statistics

Minimum	1105364
5-th percentile	1149540.05
Q1	1321398
median	1529114.5
Q3	1707751.75
95-th percentile	1861018.85
Maximum	1903505
Range	798141
Interquartile range (IQR)	386353.75

Descriptive statistics

Standard deviation	228676.3733
Coefficient of variation (CV)	0.1509651048
Kurtosis	-1.167938801
Mean	1514763.121
Median Absolute Deviation (MAD)	192824.5
Skewness	-0.08540877521
Sum	1514763121
Variance	5.229288373 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1469590	1	0.1%
1554792	1	0.1%
1439887	1	0.1%
1237671	1	0.1%
1352279	1	0.1%
1409197	1	0.1%
1448066	1	0.1%
1337177	1	0.1%
1199661	1	0.1%
1483329	1	0.1%
Other values (990)	990	99.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1105364	1	0.1%
1106411	1	0.1%
1106688	1	0.1%
1106801	1	0.1%
1107910	1	0.1%
1109612	1	0.1%
1109861	1	0.1%
1112826	1	0.1%
1113231	1	0.1%
1113703	1	0.1%

Value	Count	Frequency (%)
1903505	1	0.1%
1902944	1	0.1%
1902571	1	0.1%
1902547	1	0.1%
1902302	1	0.1%
1901818	1	0.1%
1901178	1	0.1%
1900089	1	0.1%
1894721	1	0.1%
1893730	1	0.1%

Primary_applicant_age_in_years
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	53
Distinct (%)	5.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	35.546

Minimum	19
Maximum	75
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	47.9 KiB

Quantile statistics

Minimum	19
5-th percentile	22
Q1	27
median	33
Q3	42
95-th percentile	60
Maximum	75
Range	56
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	11.37546857
Coefficient of variation (CV)	0.3200210593
Kurtosis	0.5957795671
Mean	35.546
Median Absolute Deviation (MAD)	7
Skewness	1.020739269
Sum	35546
Variance	129.4012853
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
27	51	5.1%
26	50	5.0%
23	48	4.8%
24	44	4.4%
28	43	4.3%
25	41	4.1%
30	40	4.0%
35	40	4.0%
36	39	3.9%
31	38	3.8%
Other values (43)	566	56.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
19	2	0.2%
20	14	1.4%
21	14	1.4%
22	27	2.7%
23	48	4.8%
24	44	4.4%
25	41	4.1%
26	50	5.0%
27	51	5.1%
28	43	4.3%

Value	Count	Frequency (%)
75	2	0.2%
74	4	0.4%
70	1	0.1%
68	3	0.3%
67	3	0.3%
66	5	0.5%
65	5	0.5%
64	5	0.5%
63	8	0.8%
62	2	0.2%

Gender
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

male	690
female	310

Length

Max length	6
Median length	4
Mean length	4.62
Min length	4

Characters and Unicode

Total characters	4620
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	male
2nd row	female
3rd row	male
4th row	male
5th row	male

Common Values

Value	Count	Frequency (%)
male	690	69.0%
female	310	31.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
male	690	69.0%
female	310	31.0%

Most occurring characters

Value	Count	Frequency (%)
e	1310	28.4%
m	1000	21.6%
a	1000	21.6%
l	1000	21.6%
f	310	6.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4620	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1310	28.4%
m	1000	21.6%
a	1000	21.6%
l	1000	21.6%
f	310	6.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4620	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1310	28.4%
m	1000	21.6%
a	1000	21.6%
l	1000	21.6%
f	310	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4620	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1310	28.4%
m	1000	21.6%
a	1000	21.6%
l	1000	21.6%
f	310	6.7%

Marital_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

single	548
divorced/separated/married	310
married/widowed	92
divorced/separated	50

Length

Max length	26
Median length	6
Mean length	13.628
Min length	6

Characters and Unicode

Total characters	13628
Distinct characters	17
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	single
2nd row	divorced/separated/married
3rd row	single
4th row	single
5th row	single

Common Values

Value	Count	Frequency (%)
single	548	54.8%
divorced/separated/married	310	31.0%
married/widowed	92	9.2%
divorced/separated	50	5.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
single	548	54.8%
divorced/separated/married	310	31.0%
married/widowed	92	9.2%
divorced/separated	50	5.0%

Most occurring characters

Value	Count	Frequency (%)
e	2122	15.6%
d	1666	12.2%
r	1524	11.2%
i	1402	10.3%
a	1122	8.2%
s	908	6.7%
/	762	5.6%
n	548	4.0%
g	548	4.0%
l	548	4.0%
Other values (7)	2478	18.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	12866	94.4%
Other Punctuation	762	5.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	2122	16.5%
d	1666	12.9%
r	1524	11.8%
i	1402	10.9%
a	1122	8.7%
s	908	7.1%
n	548	4.3%
g	548	4.3%
l	548	4.3%
o	452	3.5%
Other values (6)	2026	15.7%

Other Punctuation

Value	Count	Frequency (%)
/	762	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12866	94.4%
Common	762	5.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	2122	16.5%
d	1666	12.9%
r	1524	11.8%
i	1402	10.9%
a	1122	8.7%
s	908	7.1%
n	548	4.3%
g	548	4.3%
l	548	4.3%
o	452	3.5%
Other values (6)	2026	15.7%

Common

Value	Count	Frequency (%)
/	762	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13628	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	2122	15.6%
d	1666	12.2%
r	1524	11.2%
i	1402	10.3%
a	1122	8.2%
s	908	6.7%
/	762	5.6%
n	548	4.0%
g	548	4.0%
l	548	4.0%
Other values (7)	2478	18.2%

Number_of_dependents
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

1	845
2	155

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
1	845	84.5%
2	155	15.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	845	84.5%
2	155	15.5%

Most occurring characters

Value	Count	Frequency (%)
1	845	84.5%
2	155	15.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	845	84.5%
2	155	15.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	845	84.5%
2	155	15.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	845	84.5%
2	155	15.5%

Housing
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

own	713
rent	179
for free	108

Length

Max length	8
Median length	3
Mean length	3.719
Min length	3

Characters and Unicode

Total characters	3719
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	own
2nd row	own
3rd row	own
4th row	for free
5th row	for free

Common Values

Value	Count	Frequency (%)
own	713	71.3%
rent	179	17.9%
for free	108	10.8%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
own	713	64.4%
rent	179	16.2%
for	108	9.7%
free	108	9.7%

Most occurring characters

Value	Count	Frequency (%)
n	892	24.0%
o	821	22.1%
w	713	19.2%
r	395	10.6%
e	395	10.6%
f	216	5.8%
t	179	4.8%
	108	2.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3611	97.1%
Space Separator	108	2.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	892	24.7%
o	821	22.7%
w	713	19.7%
r	395	10.9%
e	395	10.9%
f	216	6.0%
t	179	5.0%

Space Separator

Value	Count	Frequency (%)
	108	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3611	97.1%
Common	108	2.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	892	24.7%
o	821	22.7%
w	713	19.7%
r	395	10.9%
e	395	10.9%
f	216	6.0%
t	179	5.0%

Common

Value	Count	Frequency (%)
	108	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3719	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	892	24.0%
o	821	22.1%
w	713	19.2%
r	395	10.6%
e	395	10.6%
f	216	5.8%
t	179	4.8%
	108	2.9%

Years_at_current_residence
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

4	413
2	308
3	149
1	130

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4
2nd row	2
3rd row	3
4th row	4
5th row	4

Common Values

Value	Count	Frequency (%)
4	413	41.3%
2	308	30.8%
3	149	14.9%
1	130	13.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
4	413	41.3%
2	308	30.8%
3	149	14.9%
1	130	13.0%

Most occurring characters

Value	Count	Frequency (%)
4	413	41.3%
2	308	30.8%
3	149	14.9%
1	130	13.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	413	41.3%
2	308	30.8%
3	149	14.9%
1	130	13.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	413	41.3%
2	308	30.8%
3	149	14.9%
1	130	13.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	413	41.3%
2	308	30.8%
3	149	14.9%
1	130	13.0%

Employment_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

skilled employee / official	630
unskilled - resident	200
management / self-employed / highly qualified employee / officer	148
unemployed / unskilled - non-resident	22

Length

Max length	64
Median length	27
Mean length	31.296
Min length	20

Characters and Unicode

Total characters	31296
Distinct characters	23
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	skilled employee / official
2nd row	skilled employee / official
3rd row	unskilled - resident
4th row	skilled employee / official
5th row	skilled employee / official

Common Values

Value	Count	Frequency (%)
skilled employee / official	630	63.0%
unskilled - resident	200	20.0%
management / self-employed / highly qualified employee / officer	148	14.8%
unemployed / unskilled - non-resident	22	2.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
	1318	28.9%
employee	778	17.1%
skilled	630	13.8%
official	630	13.8%
unskilled	222	4.9%
resident	200	4.4%
management	148	3.2%
self-employed	148	3.2%
highly	148	3.2%
qualified	148	3.2%
Other values (3)	192	4.2%

Most occurring characters

Value	Count	Frequency (%)
e	4710	15.0%
l	3726	11.9%
	3562	11.4%
i	2926	9.3%
f	1852	5.9%
o	1748	5.6%
d	1392	4.4%
m	1244	4.0%
s	1222	3.9%
y	1096	3.5%
Other values (13)	7818	25.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	26246	83.9%
Space Separator	3562	11.4%
Other Punctuation	1096	3.5%
Dash Punctuation	392	1.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	4710	17.9%
l	3726	14.2%
i	2926	11.1%
f	1852	7.1%
o	1748	6.7%
d	1392	5.3%
m	1244	4.7%
s	1222	4.7%
y	1096	4.2%
a	1074	4.1%
Other values (10)	5256	20.0%

Space Separator

Value	Count	Frequency (%)
	3562	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	1096	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	392	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	26246	83.9%
Common	5050	16.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	4710	17.9%
l	3726	14.2%
i	2926	11.1%
f	1852	7.1%
o	1748	6.7%
d	1392	5.3%
m	1244	4.7%
s	1222	4.7%
y	1096	4.2%
a	1074	4.1%
Other values (10)	5256	20.0%

Common

Value	Count	Frequency (%)
	3562	70.5%
/	1096	21.7%
-	392	7.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	31296	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	4710	15.0%
l	3726	11.9%
	3562	11.4%
i	2926	9.3%
f	1852	5.9%
o	1748	5.6%
d	1392	4.4%
m	1244	4.0%
s	1222	3.9%
y	1096	3.5%
Other values (13)	7818	25.0%

Has_been_employed_for_at_least
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	0.4%
Missing	62
Missing (%)	6.2%
Memory size	47.9 KiB

1 year	339
7 years	253
4 years	174
0 year	172

Length

Max length	7
Median length	6
Mean length	6.455223881
Min length	6

Characters and Unicode

Total characters	6055
Distinct characters	10
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	7 years
2nd row	1 year
3rd row	4 years
4th row	4 years
5th row	1 year

Common Values

Value	Count	Frequency (%)
1 year	339	33.9%
7 years	253	25.3%
4 years	174	17.4%
0 year	172	17.2%
(Missing)	62	6.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
year	511	27.2%
years	427	22.8%
1	339	18.1%
7	253	13.5%
4	174	9.3%
0	172	9.2%

Most occurring characters

Value	Count	Frequency (%)
	938	15.5%
y	938	15.5%
e	938	15.5%
a	938	15.5%
r	938	15.5%
s	427	7.1%
1	339	5.6%
7	253	4.2%
4	174	2.9%
0	172	2.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4179	69.0%
Space Separator	938	15.5%
Decimal Number	938	15.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
y	938	22.4%
e	938	22.4%
a	938	22.4%
r	938	22.4%
s	427	10.2%

Decimal Number

Value	Count	Frequency (%)
1	339	36.1%
7	253	27.0%
4	174	18.6%
0	172	18.3%

Space Separator

Value	Count	Frequency (%)
	938	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4179	69.0%
Common	1876	31.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	938	50.0%
1	339	18.1%
7	253	13.5%
4	174	9.3%
0	172	9.2%

Latin

Value	Count	Frequency (%)
y	938	22.4%
e	938	22.4%
a	938	22.4%
r	938	22.4%
s	427	10.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6055	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	938	15.5%
y	938	15.5%
e	938	15.5%
a	938	15.5%
r	938	15.5%
s	427	7.1%
1	339	5.6%
7	253	4.2%
4	174	2.9%
0	172	2.8%

Has_been_employed_for_at_most
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	0.5%
Missing	253
Missing (%)	25.3%
Memory size	47.9 KiB

4 years	339
7 years	174
1 year	172
0 year	62

Length

Max length	7
Median length	7
Mean length	6.686746988
Min length	6

Characters and Unicode

Total characters	4995
Distinct characters	10
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4 years
2nd row	7 years
3rd row	7 years
4th row	4 years
5th row	4 years

Common Values

Value	Count	Frequency (%)
4 years	339	33.9%
7 years	174	17.4%
1 year	172	17.2%
0 year	62	6.2%
(Missing)	253	25.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
years	513	34.3%
4	339	22.7%
year	234	15.7%
7	174	11.6%
1	172	11.5%
0	62	4.1%

Most occurring characters

Value	Count	Frequency (%)
	747	15.0%
y	747	15.0%
e	747	15.0%
a	747	15.0%
r	747	15.0%
s	513	10.3%
4	339	6.8%
7	174	3.5%
1	172	3.4%
0	62	1.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3501	70.1%
Space Separator	747	15.0%
Decimal Number	747	15.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
y	747	21.3%
e	747	21.3%
a	747	21.3%
r	747	21.3%
s	513	14.7%

Decimal Number

Value	Count	Frequency (%)
4	339	45.4%
7	174	23.3%
1	172	23.0%
0	62	8.3%

Space Separator

Value	Count	Frequency (%)
	747	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3501	70.1%
Common	1494	29.9%

Most frequent character per script

Common

Value	Count	Frequency (%)
	747	50.0%
4	339	22.7%
7	174	11.6%
1	172	11.5%
0	62	4.1%

Latin

Value	Count	Frequency (%)
y	747	21.3%
e	747	21.3%
a	747	21.3%
r	747	21.3%
s	513	14.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4995	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	747	15.0%
y	747	15.0%
e	747	15.0%
a	747	15.0%
r	747	15.0%
s	513	10.3%
4	339	6.8%
7	174	3.5%
1	172	3.4%
0	62	1.2%

Telephone
Categorical

CONSTANT
HIGH CORRELATION
MISSING
REJECTED

Distinct	1
Distinct (%)	0.2%
Missing	596
Missing (%)	59.6%
Memory size	47.9 KiB

Registered under the applicant's name	404

Length

Max length	37
Median length	37
Mean length	37
Min length	37

Characters and Unicode

Total characters	14948
Distinct characters	18
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Registered under the applicant's name
2nd row	Registered under the applicant's name
3rd row	Registered under the applicant's name
4th row	Registered under the applicant's name
5th row	Registered under the applicant's name

Common Values

Value	Count	Frequency (%)
Registered under the applicant's name	404	40.4%
(Missing)	596	59.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
registered	404	20.0%
under	404	20.0%
the	404	20.0%
applicant's	404	20.0%
name	404	20.0%

Most occurring characters

Value	Count	Frequency (%)
e	2424	16.2%
	1616	10.8%
t	1212	8.1%
n	1212	8.1%
a	1212	8.1%
i	808	5.4%
s	808	5.4%
r	808	5.4%
d	808	5.4%
p	808	5.4%
Other values (8)	3232	21.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	12524	83.8%
Space Separator	1616	10.8%
Uppercase Letter	404	2.7%
Other Punctuation	404	2.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	2424	19.4%
t	1212	9.7%
n	1212	9.7%
a	1212	9.7%
i	808	6.5%
s	808	6.5%
r	808	6.5%
d	808	6.5%
p	808	6.5%
l	404	3.2%
Other values (5)	2020	16.1%

Space Separator

Value	Count	Frequency (%)
	1616	100.0%

Uppercase Letter

Value	Count	Frequency (%)
R	404	100.0%

Other Punctuation

Value	Count	Frequency (%)
'	404	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12928	86.5%
Common	2020	13.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	2424	18.8%
t	1212	9.4%
n	1212	9.4%
a	1212	9.4%
i	808	6.2%
s	808	6.2%
r	808	6.2%
d	808	6.2%
p	808	6.2%
R	404	3.1%
Other values (6)	2424	18.8%

Common

Value	Count	Frequency (%)
	1616	80.0%
'	404	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	14948	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	2424	16.2%
	1616	10.8%
t	1212	8.1%
n	1212	8.1%
a	1212	8.1%
i	808	5.4%
s	808	5.4%
r	808	5.4%
d	808	5.4%
p	808	5.4%
Other values (8)	3232	21.6%

Foreign_worker
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

1	963
0	37

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	963	96.3%
0	37	3.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	963	96.3%
0	37	3.7%

Most occurring characters

Value	Count	Frequency (%)
1	963	96.3%
0	37	3.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	963	96.3%
0	37	3.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	963	96.3%
0	37	3.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	963	96.3%
0	37	3.7%

Savings_account_balance
Categorical

HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	0.5%
Missing	183
Missing (%)	18.3%
Memory size	47.9 KiB

Low	603
Medium	103
High	63
Very high	48

Length

Max length	9
Median length	3
Mean length	3.807833537
Min length	3

Characters and Unicode

Total characters	3111
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Low
2nd row	Low
3rd row	Low
4th row	Low
5th row	High

Common Values

Value	Count	Frequency (%)
Low	603	60.3%
Medium	103	10.3%
High	63	6.3%
Very high	48	4.8%
(Missing)	183	18.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
low	603	69.7%
high	111	12.8%
medium	103	11.9%
very	48	5.5%

Most occurring characters

Value	Count	Frequency (%)
L	603	19.4%
o	603	19.4%
w	603	19.4%
i	214	6.9%
h	159	5.1%
e	151	4.9%
g	111	3.6%
M	103	3.3%
d	103	3.3%
u	103	3.3%
Other values (6)	358	11.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2246	72.2%
Uppercase Letter	817	26.3%
Space Separator	48	1.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	603	26.8%
w	603	26.8%
i	214	9.5%
h	159	7.1%
e	151	6.7%
g	111	4.9%
d	103	4.6%
u	103	4.6%
m	103	4.6%
r	48	2.1%

Uppercase Letter

Value	Count	Frequency (%)
L	603	73.8%
M	103	12.6%
H	63	7.7%
V	48	5.9%

Space Separator

Value	Count	Frequency (%)
	48	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3063	98.5%
Common	48	1.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
L	603	19.7%
o	603	19.7%
w	603	19.7%
i	214	7.0%
h	159	5.2%
e	151	4.9%
g	111	3.6%
M	103	3.4%
d	103	3.4%
u	103	3.4%
Other values (5)	310	10.1%

Common

Value	Count	Frequency (%)
	48	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3111	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
L	603	19.4%
o	603	19.4%
w	603	19.4%
i	214	6.9%
h	159	5.1%
e	151	4.9%
g	111	3.6%
M	103	3.3%
d	103	3.3%
u	103	3.3%
Other values (6)	358	11.5%

Balance_in_existing_bank_account_(lower_limit_of_bucket)
Categorical

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.6%
Missing	668
Missing (%)	66.8%
Memory size	47.9 KiB

0	269
2 lac	63

Length

Max length	5
Median length	1
Mean length	1.759036145
Min length	1

Characters and Unicode

Total characters	584
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	269	26.9%
2 lac	63	6.3%
(Missing)	668	66.8%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	269	68.1%
2	63	15.9%
lac	63	15.9%

Most occurring characters

Value	Count	Frequency (%)
0	269	46.1%
2	63	10.8%
	63	10.8%
l	63	10.8%
a	63	10.8%
c	63	10.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	332	56.8%
Lowercase Letter	189	32.4%
Space Separator	63	10.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	63	33.3%
a	63	33.3%
c	63	33.3%

Decimal Number

Value	Count	Frequency (%)
0	269	81.0%
2	63	19.0%

Space Separator

Value	Count	Frequency (%)
	63	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	395	67.6%
Latin	189	32.4%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	269	68.1%
2	63	15.9%
	63	15.9%

Latin

Value	Count	Frequency (%)
l	63	33.3%
a	63	33.3%
c	63	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	584	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	269	46.1%
2	63	10.8%
	63	10.8%
l	63	10.8%
a	63	10.8%
c	63	10.8%

Balance_in_existing_bank_account_(upper_limit_of_bucket)
Categorical

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.4%
Missing	457
Missing (%)	45.7%
Memory size	47.9 KiB

0	274
2 lac	269

Length

Max length	5
Median length	1
Mean length	2.981583794
Min length	1

Characters and Unicode

Total characters	1619
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	2 lac
3rd row	0
4th row	0
5th row	2 lac

Common Values

Value	Count	Frequency (%)
0	274	27.4%
2 lac	269	26.9%
(Missing)	457	45.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	274	33.7%
2	269	33.1%
lac	269	33.1%

Most occurring characters

Value	Count	Frequency (%)
0	274	16.9%
2	269	16.6%
	269	16.6%
l	269	16.6%
a	269	16.6%
c	269	16.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	807	49.8%
Decimal Number	543	33.5%
Space Separator	269	16.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	269	33.3%
a	269	33.3%
c	269	33.3%

Decimal Number

Value	Count	Frequency (%)
0	274	50.5%
2	269	49.5%

Space Separator

Value	Count	Frequency (%)
	269	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	812	50.2%
Latin	807	49.8%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	274	33.7%
2	269	33.1%
	269	33.1%

Latin

Value	Count	Frequency (%)
l	269	33.3%
a	269	33.3%
c	269	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1619	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	274	16.9%
2	269	16.6%
	269	16.6%
l	269	16.6%
a	269	16.6%
c	269	16.6%

loan_application_id
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

d68d975e-edad-11ea-8761-1d6f9c1ff461	1
d68f0dd2-edad-11ea-8785-076f1a6b0e1d	1
d68f06d4-edad-11ea-8933-08c4e91e1cae	1
d68f0760-edad-11ea-9800-185713046169	1
d68f07ec-edad-11ea-b6db-3496b8dbd5c8	1
Other values (995)	995

Length

Max length	36
Median length	36
Mean length	36
Min length	36

Characters and Unicode

Total characters	36000
Distinct characters	17
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	d68d975e-edad-11ea-8761-1d6f9c1ff461
2nd row	d68d989e-edad-11ea-b1d5-2bcf65006448
3rd row	d68d995c-edad-11ea-814a-1b6716782575
4th row	d68d99fc-edad-11ea-8841-17e8848060ae
5th row	d68d9a92-edad-11ea-9f3d-1f8682db006a

Common Values

Value	Count	Frequency (%)
d68d975e-edad-11ea-8761-1d6f9c1ff461	1	0.1%
d68f0dd2-edad-11ea-8785-076f1a6b0e1d	1	0.1%
d68f06d4-edad-11ea-8933-08c4e91e1cae	1	0.1%
d68f0760-edad-11ea-9800-185713046169	1	0.1%
d68f07ec-edad-11ea-b6db-3496b8dbd5c8	1	0.1%
d68f086e-edad-11ea-a24f-12b786b3a993	1	0.1%
d68f08fa-edad-11ea-981a-51ccea0b8718	1	0.1%
d68f0986-edad-11ea-802f-20d1fc935ad1	1	0.1%
d68f0a08-edad-11ea-9f98-4c6666986d43	1	0.1%
d68f0a94-edad-11ea-a0cb-4ef9f8e6c478	1	0.1%
Other values (990)	990	99.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
d68d975e-edad-11ea-8761-1d6f9c1ff461	1	0.1%
d68d9f74-edad-11ea-bd59-102afb4e8303	1	0.1%
d68da88e-edad-11ea-911c-45363b9e71a7	1	0.1%
d68da802-edad-11ea-8fb1-430f7bd15180	1	0.1%
d68d995c-edad-11ea-814a-1b6716782575	1	0.1%
d68d99fc-edad-11ea-8841-17e8848060ae	1	0.1%
d68d9a92-edad-11ea-9f3d-1f8682db006a	1	0.1%
d68d9b1e-edad-11ea-8b43-2b6a0308d487	1	0.1%
d68d9bb4-edad-11ea-bb16-0490ef14f12e	1	0.1%
d68d9c40-edad-11ea-b46c-5067ccf3672a	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
d	4273	11.9%
-	4000	11.1%
e	3575	9.9%
a	3492	9.7%
1	3231	9.0%
8	2452	6.8%
6	2149	6.0%
f	1406	3.9%
2	1380	3.8%
4	1373	3.8%
Other values (7)	8669	24.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16755	46.5%
Lowercase Letter	15245	42.3%
Dash Punctuation	4000	11.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	3231	19.3%
8	2452	14.6%
6	2149	12.8%
2	1380	8.2%
4	1373	8.2%
0	1358	8.1%
9	1331	7.9%
3	1268	7.6%
5	1161	6.9%
7	1052	6.3%

Lowercase Letter

Value	Count	Frequency (%)
d	4273	28.0%
e	3575	23.5%
a	3492	22.9%
f	1406	9.2%
b	1334	8.8%
c	1165	7.6%

Dash Punctuation

Value	Count	Frequency (%)
-	4000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	20755	57.7%
Latin	15245	42.3%

Most frequent character per script

Common

Value	Count	Frequency (%)
-	4000	19.3%
1	3231	15.6%
8	2452	11.8%
6	2149	10.4%
2	1380	6.6%
4	1373	6.6%
0	1358	6.5%
9	1331	6.4%
3	1268	6.1%
5	1161	5.6%

Latin

Value	Count	Frequency (%)
d	4273	28.0%
e	3575	23.5%
a	3492	22.9%
f	1406	9.2%
b	1334	8.8%
c	1165	7.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	36000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
d	4273	11.9%
-	4000	11.1%
e	3575	9.9%
a	3492	9.7%
1	3231	9.0%
8	2452	6.8%
6	2149	6.0%
f	1406	3.9%
2	1380	3.8%
4	1373	3.8%
Other values (7)	8669	24.1%

Months_loan_taken_for
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	33
Distinct (%)	3.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	20.903

Minimum	4
Maximum	72
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	47.9 KiB

Quantile statistics

Minimum	4
5-th percentile	6
Q1	12
median	18
Q3	24
95-th percentile	48
Maximum	72
Range	68
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	12.05881445
Coefficient of variation (CV)	0.5768939603
Kurtosis	0.9197813601
Mean	20.903
Median Absolute Deviation (MAD)	6
Skewness	1.094184172
Sum	20903
Variance	145.415006
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
24	184	18.4%
12	179	17.9%
18	113	11.3%
36	83	8.3%
6	75	7.5%
15	64	6.4%
9	49	4.9%
48	48	4.8%
30	40	4.0%
21	30	3.0%
Other values (23)	135	13.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4	6	0.6%
5	1	0.1%
6	75	7.5%
7	5	0.5%
8	7	0.7%
9	49	4.9%
10	28	2.8%
11	9	0.9%
12	179	17.9%
13	4	0.4%

Value	Count	Frequency (%)
72	1	0.1%
60	13	1.3%
54	2	0.2%
48	48	4.8%
47	1	0.1%
45	5	0.5%
42	11	1.1%
40	1	0.1%
39	5	0.5%
36	83	8.3%

Purpose
Categorical

HIGH CORRELATION
MISSING

Distinct	9
Distinct (%)	0.9%
Missing	12
Missing (%)	1.2%
Memory size	47.9 KiB

electronic equipment	280
new vehicle	234
FF&E	181
used vehicle	103
business	97
Other values (4)	93

Length

Max length	20
Median length	19
Mean length	12.15991903
Min length	4

Characters and Unicode

Total characters	12014
Distinct characters	23
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	electronic equipment
2nd row	electronic equipment
3rd row	education
4th row	FF&E
5th row	new vehicle

Common Values

Value	Count	Frequency (%)
electronic equipment	280	28.0%
new vehicle	234	23.4%
FF&E	181	18.1%
used vehicle	103	10.3%
business	97	9.7%
education	50	5.0%
repair costs	22	2.2%
domestic appliances	12	1.2%
career development	9	0.9%
(Missing)	12	1.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
vehicle	337	20.4%
electronic	280	17.0%
equipment	280	17.0%
new	234	14.2%
ff&e	181	11.0%
used	103	6.2%
business	97	5.9%
education	50	3.0%
repair	22	1.3%
costs	22	1.3%
Other values (4)	42	2.5%

Most occurring characters

Value	Count	Frequency (%)
e	2369	19.7%
i	1090	9.1%
c	1002	8.3%
n	962	8.0%
	660	5.5%
t	653	5.4%
l	638	5.3%
u	530	4.4%
s	462	3.8%
o	373	3.1%
Other values (13)	3275	27.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10630	88.5%
Space Separator	660	5.5%
Uppercase Letter	543	4.5%
Other Punctuation	181	1.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	2369	22.3%
i	1090	10.3%
c	1002	9.4%
n	962	9.0%
t	653	6.1%
l	638	6.0%
u	530	5.0%
s	462	4.3%
o	373	3.5%
v	346	3.3%
Other values (9)	2205	20.7%

Uppercase Letter

Value	Count	Frequency (%)
F	362	66.7%
E	181	33.3%

Space Separator

Value	Count	Frequency (%)
	660	100.0%

Other Punctuation

Value	Count	Frequency (%)
&	181	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	11173	93.0%
Common	841	7.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	2369	21.2%
i	1090	9.8%
c	1002	9.0%
n	962	8.6%
t	653	5.8%
l	638	5.7%
u	530	4.7%
s	462	4.1%
o	373	3.3%
F	362	3.2%
Other values (11)	2732	24.5%

Common

Value	Count	Frequency (%)
	660	78.5%
&	181	21.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12014	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	2369	19.7%
i	1090	9.1%
c	1002	8.3%
n	962	8.0%
	660	5.5%
t	653	5.4%
l	638	5.3%
u	530	4.4%
s	462	3.8%
o	373	3.1%
Other values (13)	3275	27.3%

Principal_loan_amount
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	921
Distinct (%)	92.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3271258

Minimum	250000
Maximum	18424000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	47.9 KiB

Quantile statistics

Minimum	250000
5-th percentile	708950
Q1	1365500
median	2319500
Q3	3972250
95-th percentile	9162700
Maximum	18424000
Range	18174000
Interquartile range (IQR)	2606750

Descriptive statistics

Standard deviation	2822736.876
Coefficient of variation (CV)	0.8628903241
Kurtosis	4.292590308
Mean	3271258
Median Absolute Deviation (MAD)	1097500
Skewness	1.94962768
Sum	3271258000
Variance	7.967843471 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1478000	3	0.3%
1262000	3	0.3%
1258000	3	0.3%
1275000	3	0.3%
1393000	3	0.3%
1442000	2	0.2%
3590000	2	0.2%
2578000	2	0.2%
701000	2	0.2%
1924000	2	0.2%
Other values (911)	975	97.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
250000	1	0.1%
276000	1	0.1%
338000	1	0.1%
339000	1	0.1%
343000	1	0.1%
362000	1	0.1%
368000	1	0.1%
385000	1	0.1%
392000	1	0.1%
409000	1	0.1%

Value	Count	Frequency (%)
18424000	1	0.1%
15945000	1	0.1%
15857000	1	0.1%
15672000	1	0.1%
15653000	1	0.1%
14896000	1	0.1%
14782000	1	0.1%
14555000	1	0.1%
14421000	1	0.1%
14318000	1	0.1%

EMI_rate_in_percentage_of_disposable_income
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

4	476
2	231
3	157
1	136

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4
2nd row	2
3rd row	2
4th row	2
5th row	3

Common Values

Value	Count	Frequency (%)
4	476	47.6%
2	231	23.1%
3	157	15.7%
1	136	13.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
4	476	47.6%
2	231	23.1%
3	157	15.7%
1	136	13.6%

Most occurring characters

Value	Count	Frequency (%)
4	476	47.6%
2	231	23.1%
3	157	15.7%
1	136	13.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	476	47.6%
2	231	23.1%
3	157	15.7%
1	136	13.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	476	47.6%
2	231	23.1%
3	157	15.7%
1	136	13.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	476	47.6%
2	231	23.1%
3	157	15.7%
1	136	13.6%

Property
Categorical

HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	0.4%
Missing	154
Missing (%)	15.4%
Memory size	47.9 KiB

car or other	332
real estate	282
building society savings agreement/life insurance	232

Length

Max length	49
Median length	12
Mean length	21.81323877
Min length	11

Characters and Unicode

Total characters	18454
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	real estate
2nd row	real estate
3rd row	real estate
4th row	building society savings agreement/life insurance
5th row	building society savings agreement/life insurance

Common Values

Value	Count	Frequency (%)
car or other	332	33.2%
real estate	282	28.2%
building society savings agreement/life insurance	232	23.2%
(Missing)	154	15.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
car	332	12.2%
or	332	12.2%
other	332	12.2%
real	282	10.4%
estate	282	10.4%
building	232	8.5%
society	232	8.5%
savings	232	8.5%
agreement/life	232	8.5%
insurance	232	8.5%

Most occurring characters

Value	Count	Frequency (%)
e	2570	13.9%
	1874	10.2%
r	1742	9.4%
a	1592	8.6%
i	1392	7.5%
t	1360	7.4%
s	1210	6.6%
n	1160	6.3%
o	896	4.9%
c	796	4.3%
Other values (11)	3862	20.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	16348	88.6%
Space Separator	1874	10.2%
Other Punctuation	232	1.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	2570	15.7%
r	1742	10.7%
a	1592	9.7%
i	1392	8.5%
t	1360	8.3%
s	1210	7.4%
n	1160	7.1%
o	896	5.5%
c	796	4.9%
l	746	4.6%
Other values (9)	2884	17.6%

Space Separator

Value	Count	Frequency (%)
	1874	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	232	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	16348	88.6%
Common	2106	11.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	2570	15.7%
r	1742	10.7%
a	1592	9.7%
i	1392	8.5%
t	1360	8.3%
s	1210	7.4%
n	1160	7.1%
o	896	5.5%
c	796	4.9%
l	746	4.6%
Other values (9)	2884	17.6%

Common

Value	Count	Frequency (%)
	1874	89.0%
/	232	11.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	18454	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	2570	13.9%
	1874	10.2%
r	1742	9.4%
a	1592	8.6%
i	1392	7.5%
t	1360	7.4%
s	1210	6.6%
n	1160	6.3%
o	896	4.9%
c	796	4.3%
Other values (11)	3862	20.9%

Has_coapplicant
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

0	959
1	41

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	959	95.9%
1	41	4.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	959	95.9%
1	41	4.1%

Most occurring characters

Value	Count	Frequency (%)
0	959	95.9%
1	41	4.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	959	95.9%
1	41	4.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	959	95.9%
1	41	4.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	959	95.9%
1	41	4.1%

Has_guarantor
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

0	948
1	52

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	948	94.8%
1	52	5.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	948	94.8%
1	52	5.2%

Most occurring characters

Value	Count	Frequency (%)
0	948	94.8%
1	52	5.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	948	94.8%
1	52	5.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	948	94.8%
1	52	5.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	948	94.8%
1	52	5.2%

Other_EMI_plans
Categorical

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	1.1%
Missing	814
Missing (%)	81.4%
Memory size	47.9 KiB

bank	139
stores	47

Length

Max length	6
Median length	4
Mean length	4.505376344
Min length	4

Characters and Unicode

Total characters	838
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	bank
2nd row	bank
3rd row	bank
4th row	stores
5th row	bank

Common Values

Value	Count	Frequency (%)
bank	139	13.9%
stores	47	4.7%
(Missing)	814	81.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
bank	139	74.7%
stores	47	25.3%

Most occurring characters

Value	Count	Frequency (%)
b	139	16.6%
a	139	16.6%
n	139	16.6%
k	139	16.6%
s	94	11.2%
t	47	5.6%
o	47	5.6%
r	47	5.6%
e	47	5.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	838	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
b	139	16.6%
a	139	16.6%
n	139	16.6%
k	139	16.6%
s	94	11.2%
t	47	5.6%
o	47	5.6%
r	47	5.6%
e	47	5.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	838	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
b	139	16.6%
a	139	16.6%
n	139	16.6%
k	139	16.6%
s	94	11.2%
t	47	5.6%
o	47	5.6%
r	47	5.6%
e	47	5.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	838	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
b	139	16.6%
a	139	16.6%
n	139	16.6%
k	139	16.6%
s	94	11.2%
t	47	5.6%
o	47	5.6%
r	47	5.6%
e	47	5.6%

Number_of_existing_loans_at_this_bank
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

1	633
2	333
3	28
4	6

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	1
3rd row	1
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
1	633	63.3%
2	333	33.3%
3	28	2.8%
4	6	0.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	633	63.3%
2	333	33.3%
3	28	2.8%
4	6	0.6%

Most occurring characters

Value	Count	Frequency (%)
1	633	63.3%
2	333	33.3%
3	28	2.8%
4	6	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	633	63.3%
2	333	33.3%
3	28	2.8%
4	6	0.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	633	63.3%
2	333	33.3%
3	28	2.8%
4	6	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	633	63.3%
2	333	33.3%
3	28	2.8%
4	6	0.6%

Loan_history
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

existing loans paid back duly till now	530
critical/pending loans at other banks	293
delay in paying off loans in the past	88
all loans at this bank paid back duly	49
no loans taken/all loans paid back duly	40

Length

Max length	39
Median length	38
Mean length	37.61
Min length	37

Characters and Unicode

Total characters	37610
Distinct characters	23
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	critical/pending loans at other banks
2nd row	existing loans paid back duly till now
3rd row	critical/pending loans at other banks
4th row	existing loans paid back duly till now
5th row	delay in paying off loans in the past

Common Values

Value	Count	Frequency (%)
existing loans paid back duly till now	530	53.0%
critical/pending loans at other banks	293	29.3%
delay in paying off loans in the past	88	8.8%
all loans at this bank paid back duly	49	4.9%
no loans taken/all loans paid back duly	40	4.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
loans	1040	15.9%
paid	619	9.4%
back	619	9.4%
duly	619	9.4%
existing	530	8.1%
till	530	8.1%
now	530	8.1%
at	342	5.2%
critical/pending	293	4.5%
other	293	4.5%
Other values (12)	1136	17.3%

Most occurring characters

Value	Count	Frequency (%)
	5551	14.8%
a	3648	9.7%
i	3401	9.0%
n	3372	9.0%
l	3278	8.7%
t	2253	6.0%
s	2000	5.3%
o	1991	5.3%
d	1619	4.3%
e	1332	3.5%
Other values (13)	9165	24.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	31726	84.4%
Space Separator	5551	14.8%
Other Punctuation	333	0.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	3648	11.5%
i	3401	10.7%
n	3372	10.6%
l	3278	10.3%
t	2253	7.1%
s	2000	6.3%
o	1991	6.3%
d	1619	5.1%
e	1332	4.2%
c	1205	3.8%
Other values (11)	7627	24.0%

Space Separator

Value	Count	Frequency (%)
	5551	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	333	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	31726	84.4%
Common	5884	15.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	3648	11.5%
i	3401	10.7%
n	3372	10.6%
l	3278	10.3%
t	2253	7.1%
s	2000	6.3%
o	1991	6.3%
d	1619	5.1%
e	1332	4.2%
c	1205	3.8%
Other values (11)	7627	24.0%

Common

Value	Count	Frequency (%)
	5551	94.3%
/	333	5.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	37610	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	5551	14.8%
a	3648	9.7%
i	3401	9.0%
n	3372	9.0%
l	3278	8.7%
t	2253	6.0%
s	2000	5.3%
o	1991	5.3%
d	1619	4.3%
e	1332	3.5%
Other values (13)	9165	24.4%

high_risk_applicant
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	47.9 KiB

0	700
1	300

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	700	70.0%
1	300	30.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	700	70.0%
1	300	30.0%

Most occurring characters

Value	Count	Frequency (%)
0	700	70.0%
1	300	30.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	700	70.0%
1	300	30.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	700	70.0%
1	300	30.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	700	70.0%
1	300	30.0%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	applicant_id	Primary_applicant_age_in_years	Gender	Marital_status	Number_of_dependents	Housing	Years_at_current_residence	Employment_status	Has_been_employed_for_at_least	Has_been_employed_for_at_most	Telephone	Foreign_worker	Savings_account_balance	Balance_in_existing_bank_account_(lower_limit_of_bucket)	Balance_in_existing_bank_account_(upper_limit_of_bucket)	loan_application_id	Months_loan_taken_for	Purpose	Principal_loan_amount	EMI_rate_in_percentage_of_disposable_income	Property	Has_guarantor	Other_EMI_plans	Number_of_existing_loans_at_this_bank	Loan_history	high_risk_applicant
0	1469590	67	male	single	1	own	4	skilled employee / official	7 years	NaN	Registered under the applicant's name	1	NaN	NaN	0	d68d975e-edad-11ea-8761-1d6f9c1ff461	6	electronic equipment	1169000	4	real estate	0	NaN	2	critical/pending loans at other banks	0
1	1203873	22	female	divorced/separated/married	1	own	2	skilled employee / official	1 year	4 years	NaN	1	Low	0	2 lac	d68d989e-edad-11ea-b1d5-2bcf65006448	48	electronic equipment	5951000	2	real estate	0	NaN	1	existing loans paid back duly till now	1
2	1432761	49	male	single	2	own	3	unskilled - resident	4 years	7 years	NaN	1	Low	NaN	NaN	d68d995c-edad-11ea-814a-1b6716782575	12	education	2096000	2	real estate	0	NaN	1	critical/pending loans at other banks	0
3	1207582	45	male	single	2	for free	4	skilled employee / official	4 years	7 years	NaN	1	Low	NaN	0	d68d99fc-edad-11ea-8841-17e8848060ae	42	FF&E	7882000	2	building society savings agreement/life insurance	1	NaN	1	existing loans paid back duly till now	0
4	1674436	53	male	single	2	for free	4	skilled employee / official	1 year	4 years	NaN	1	Low	NaN	0	d68d9a92-edad-11ea-9f3d-1f8682db006a	24	new vehicle	4870000	3	NaN	0	NaN	2	delay in paying off loans in the past	1
5	1213971	35	male	single	2	for free	4	unskilled - resident	1 year	4 years	Registered under the applicant's name	1	NaN	NaN	NaN	d68d9b1e-edad-11ea-8b43-2b6a0308d487	36	education	9055000	2	NaN	0	NaN	1	existing loans paid back duly till now	0
6	1428822	53	male	single	1	own	4	skilled employee / official	7 years	NaN	NaN	1	High	NaN	NaN	d68d9bb4-edad-11ea-bb16-0490ef14f12e	24	FF&E	2835000	3	building society savings agreement/life insurance	0	NaN	1	existing loans paid back duly till now	0
7	1705739	35	male	single	1	rent	2	management / self-employed / highly qualified employee / officer	1 year	4 years	Registered under the applicant's name	1	Low	0	2 lac	d68d9c40-edad-11ea-b46c-5067ccf3672a	36	used vehicle	6948000	2	car or other	0	NaN	1	existing loans paid back duly till now	0
8	1715169	61	male	divorced/separated	1	own	4	unskilled - resident	4 years	7 years	NaN	1	Very high	NaN	NaN	d68d9cc2-edad-11ea-95a3-19eea692401f	12	electronic equipment	3059000	2	real estate	0	NaN	1	existing loans paid back duly till now	0
9	1722991	28	male	married/widowed	1	own	2	management / self-employed / highly qualified employee / officer	NaN	0 year	NaN	1	Low	0	2 lac	d68d9d4e-edad-11ea-99f2-2c0022cf7ade	30	new vehicle	5234000	4	car or other	0	NaN	2	critical/pending loans at other banks	1

Last rows

	applicant_id	Primary_applicant_age_in_years	Gender	Marital_status	Number_of_dependents	Housing	Years_at_current_residence	Employment_status	Has_been_employed_for_at_least	Has_been_employed_for_at_most	Telephone	Foreign_worker	Savings_account_balance	Balance_in_existing_bank_account_(lower_limit_of_bucket)	Balance_in_existing_bank_account_(upper_limit_of_bucket)	loan_application_id	Months_loan_taken_for	Purpose	Principal_loan_amount	EMI_rate_in_percentage_of_disposable_income	Property	Other_EMI_plans	Number_of_existing_loans_at_this_bank	Loan_history	high_risk_applicant
990	1354034	37	male	single	2	own	1	unskilled - resident	0 year	1 year	NaN	1	NaN	NaN	NaN	d68fb912-edad-11ea-a2a8-40ec8a427ec2	12	education	3565000	2	building society savings agreement/life insurance	NaN	2	critical/pending loans at other banks	0
991	1365267	34	male	single	2	own	4	unskilled - resident	7 years	NaN	NaN	1	Medium	NaN	NaN	d68fb99e-edad-11ea-b9a9-15d10df9edbb	15	electronic equipment	1569000	4	car or other	bank	1	all loans at this bank paid back duly	0
992	1237705	23	male	married/widowed	1	rent	4	unskilled - resident	4 years	7 years	NaN	1	NaN	NaN	0	d68fba20-edad-11ea-bb04-189bfb8e51dd	18	electronic equipment	1936000	2	car or other	NaN	2	existing loans paid back duly till now	0
993	1609685	30	male	single	1	own	3	management / self-employed / highly qualified employee / officer	NaN	0 year	Registered under the applicant's name	1	Low	NaN	0	d68fbaa2-edad-11ea-b849-58397a50baa9	36	FF&E	3959000	4	building society savings agreement/life insurance	NaN	1	existing loans paid back duly till now	0
994	1615010	50	male	single	1	own	3	skilled employee / official	7 years	NaN	Registered under the applicant's name	1	NaN	NaN	NaN	d68fbb24-edad-11ea-8782-4ba4a1f08b11	12	new vehicle	2390000	4	car or other	NaN	1	existing loans paid back duly till now	0
995	1880194	31	female	divorced/separated/married	1	own	4	unskilled - resident	4 years	7 years	NaN	1	Low	NaN	NaN	d68fbba6-edad-11ea-80fe-30b2f9300e3d	12	FF&E	1736000	3	real estate	NaN	1	existing loans paid back duly till now	0
996	1114064	40	male	divorced/separated	1	own	4	management / self-employed / highly qualified employee / officer	1 year	4 years	Registered under the applicant's name	1	Low	NaN	0	d68fbc28-edad-11ea-bc62-4240ac0824fa	30	used vehicle	3857000	4	building society savings agreement/life insurance	NaN	1	existing loans paid back duly till now	0
997	1758046	38	male	single	1	own	4	skilled employee / official	7 years	NaN	NaN	1	Low	NaN	NaN	d68fbcaa-edad-11ea-aafc-2de1139e42cd	12	electronic equipment	804000	4	car or other	NaN	1	existing loans paid back duly till now	0
998	1824545	23	male	single	1	for free	4	skilled employee / official	1 year	4 years	Registered under the applicant's name	1	Low	NaN	0	d68fbd2c-edad-11ea-b49e-2894666f2df6	45	electronic equipment	1845000	4	NaN	NaN	1	existing loans paid back duly till now	1
999	1660770	27	male	single	1	own	4	skilled employee / official	NaN	0 year	NaN	1	Medium	0	2 lac	d68fbdae-edad-11ea-a2ea-1c661d77d225	45	used vehicle	4576000	3	car or other	NaN	1	critical/pending loans at other banks	0

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Other Punctuation